Exploring a model of skillful engagement in nursing practice

Prominent challenges facing nurse leaders are the growing shortage of nurses and the increasingly complex care required by acutely ill patients. In organizations that shortage is exacerbated by turnover and intent to leave. Unsatisfactory working conditions are cited by nurses when they leave their current jobs. Disengagement from the job leads to plateaued performance, decreased organizational commitment, and increased turnover. Solutions to these challenges include methods both to retain and to increase the effectiveness of each nurse. ^ The specific aim of this study was to examine the relationships among organizational structures thought to foster the clinical development of the nurse, with indicators of the development of clinical expertise, resulting in outcomes of positive job attitudes and effectiveness. Causal loop modeling is incorporated as a systems tool to examine developmental cycles both for an organization and for an individual nurse to look beyond singular events and investigate deeper patterns that emerge over time. ^ The setting is an academic specialty-care institution, and the sample in this cross-sectional study consists of paired data from 225 RNs and their nurse managers. Two panels of survey instruments were created based on the model's theoretical variables, one completed by RNs and the other by their Nurse Managers. The RN survey panel examined the variables of structural empowerment, magnet essentials, knowledge as identified by the Benner developmental stage, psychological empowerment, job stage, engagement, intent to leave, job satisfaction and the early recognition of patient complications. The nurse manager survey panel examined the Benner developmental stage, job stage, and overall level of nursing performance. ^ Four regression models were created based on the outcome variables. Each model identified significant organizational and individual characteristics that predicted higher job satisfaction, decreased intent to leave, more effectiveness as measured by early recognition and acting upon subtle patient complications, and better job performance. ^ Implications for improving job attitudes and effectiveness focus on ways that nursing leaders can foster a more empowering and healthy work environment. ^

The INO80 chromatin remodeling complex is involved in the nucleotide excision repair pathway

The genomic DNA of eukaryotic cells is well organized into chromatin structures. However, these repressed structures present barriers that block the access of regulatory factors to the genome during various nuclear events. To overcome the obstacle, two major cellular processes, post-modification of histone tails and ATP-dependent chromatin remodeling, are involved in reconfiguring chromatin structure and creating accessible DNA. Despite the current research progress, much remains to be explored concerning the relationship between chromatin remodeling and DNA repair. Recently, one member of the ATP-dependent chromatin remodeling complexes, INO80, has been found to play a crucial role in DNA damage repair. However, the functions of this complex in higher eukaryotes have yet to be determined. The goal of my study is to generate a human somatic INO80 conditional knockout model and investigate the functions of Ino80 in damage repair.^ By homologous targeting of the INO80 locus in human HCT116 colon epithelial cells, I established a human somatic INO80 conditional knockout model. I have demonstrated that the conditional INO80 cells exhibited a sufficiently viable period when the INO80 protein is removed. Moreover, I found that loss of INO80 resulted in deficient UV lesion repair in response to UV while the protein levels of the NER factors such as XPC, XPA, XPD were not affected. And in vitro repair synthesis assay showed that the NER incision and repair synthesis activities were intact in the absence of INO80. Examination on the damage recognition factor XPC showed its recruitment to damage sites was impaired in the INO80 mutant cells. Loss of INO80 also led to reduced enrichment of XPA at the site of UV lesions. Despite the reduced recruitment of XPC and XPA observed in INO80 mutants, no direct interaction was detected. Meanwhile, direct interaction between INO80 and DDB1, the initial UV lesion detector, was detected by coimmunoprecipitation. UV-induced chromosome relaxation was reduced in cells devoid of INO80. These results demonstrate the INO80 complex may participates in the NER by interacting with DDB1 and having a critical role of in creating DNA accessibility for the nucleotide excision pathway. ^

Establishment of a complex inflammatory and protumorigenic microenvironment in mouse pancreas through cyclooxygenase-2 overexpression

Chronic inflammation is an established risk factor in the pathogenesis of many cancers. Pancreatic ductal adenocarcinoma, a malignancy with a particularly dismal prognosis, is no exception. Cyclooxygenase-2, a key enzyme induced by tissue injury, has a critical role in the generation of bioactive lipids known as prostaglandins. COX-2 overexpression is a frequent finding in pancreatic cancer, chronic pancreatitis and pancreatic intraepithelial neoplasias. To explore mechanisms through which chronic inflammation establishes and maintains a protumorigenic environment, we designed a mouse model overexpressing COX-2 in pancreatic parenchyma (BK5.COX-2 mice). We discovered that constitutive expression of COX-2 has a number of important sequelae, including upregulation of additional eicosanoid-generating enzymes and proinflammatory cytokines. Many of these molecular alterations precede the onset of significant histopathological changes. Increased levels of prostaglandins E2, D2, and F2α, 5-, 12-, and 15-hydroxyeiosatetraenoic acid (HETEs) were documented in tumors and pancreata of younger transgenic mice. Using a TaqMan™ Mouse Immune Panel, we detected elevated mRNAs for a number of proinflammatory cytokines (e.g., TNFα, IL-1β, IL-6). ^ Histological examination revealed early changes in the pancreas with similarities to human chronic pancreatitis, including loss of acinar cells, appearance of metaplastic ducts, and increased deposition of stroma. As the lesions progress, features typical of dysplastic and neoplastic cells emerged within the metaplastic ductal complexes, including cellular and nuclear atypia, crowding of cells, and loss of normal tissue architecture. The amount of fibroinflammatory stroma increased considerably; numerous small vessels were evident. A number of immunocytes from both the myeloid and lymphoid lineages were identified in transgenic pancreata. Neutrophils were the earliest to infiltrate, followed shortly by macrophages and mast cells. B and T cells generally began to appear by 8–12 weeks, and organized aggregates of lymphoid cells were often found in advanced lesions. ^ We tested the efficacy of several chemopreventive agents in this model, including celecoxib, a COX-2 selective inhibitor, pentoxifylline, a cytokine inhibitor, curcumin, a polyphenol with antioxidant and anti-inflammatory properties, and GW2974, a dual EGFR/ErbB2 inhibitor. Effects on lesion development were modest in the GW2974 and pentoxifylline treated groups, but significant prevention effects were observed with curcumin and celecoxib. ^

Assessment of the effect on statistical power of regression model misspecification by using techniques of mathematical statistics and simulation study

Objectives. This paper seeks to assess the effect on statistical power of regression model misspecification in a variety of situations. ^ Methods and results. The effect of misspecification in regression can be approximated by evaluating the correlation between the correct specification and the misspecification of the outcome variable (Harris 2010).In this paper, three misspecified models (linear, categorical and fractional polynomial) were considered. In the first section, the mathematical method of calculating the correlation between correct and misspecified models with simple mathematical forms was derived and demonstrated. In the second section, data from the National Health and Nutrition Examination Survey (NHANES 2007-2008) were used to examine such correlations. Our study shows that comparing to linear or categorical models, the fractional polynomial models, with the higher correlations, provided a better approximation of the true relationship, which was illustrated by LOESS regression. In the third section, we present the results of simulation studies that demonstrate overall misspecification in regression can produce marked decreases in power with small sample sizes. However, the categorical model had greatest power, ranging from 0.877 to 0.936 depending on sample size and outcome variable used. The power of fractional polynomial model was close to that of linear model, which ranged from 0.69 to 0.83, and appeared to be affected by the increased degrees of freedom of this model.^ Conclusion. Correlations between alternative model specifications can be used to provide a good approximation of the effect on statistical power of misspecification when the sample size is large. When model specifications have known simple mathematical forms, such correlations can be calculated mathematically. Actual public health data from NHANES 2007-2008 were used as examples to demonstrate the situations with unknown or complex correct model specification. Simulation of power for misspecified models confirmed the results based on correlation methods but also illustrated the effect of model degrees of freedom on power.^

A Bayesian approach to estimating the regression coefficients of a multinomial logit model

A Bayesian approach to estimation of the regression coefficients of a multinominal logit model with ordinal scale response categories is presented. A Monte Carlo method is used to construct the posterior distribution of the link function. The link function is treated as an arbitrary scalar function. Then the Gauss-Markov theorem is used to determine a function of the link which produces a random vector of coefficients. The posterior distribution of the random vector of coefficients is used to estimate the regression coefficients. The method described is referred to as a Bayesian generalized least square (BGLS) analysis. Two cases involving multinominal logit models are described. Case I involves a cumulative logit model and Case II involves a proportional-odds model. All inferences about the coefficients for both cases are described in terms of the posterior distribution of the regression coefficients. The results from the BGLS method are compared to maximum likelihood estimates of the regression coefficients. The BGLS method avoids the nonlinear problems encountered when estimating the regression coefficients of a generalized linear model. The method is not complex or computationally intensive. The BGLS method offers several advantages over Bayesian approaches. ^

Role of {\it Mycobacterium avium-intracellulare\/} complex infection in AIDS mortality

Disseminated MAC (dMAC) is the third most prevalent opportunistic infection in AIDS patients. In order to understand the role MAC infection plays in affecting survival of AIDS patients, a cohort of 203 suspected dMAC veterans seen at the Houston Veterans Affairs Medical Center between August 14, 1987 and December 31, 1991 were analyzed. The criteria for suspected dMAC infection was HIV+ men having a CD4+ level $\le$200 cells/mm$\sp3,$ on zidovudine treatment $\ge$1 month and who had any of the following: (a) a confirmed respiratory MAC infection, (b) fever $\ge$101$\sp\circ\rm F$ for $\ge$48 hours, (c) unexplained weight loss of 10 lbs or $\ge$10% BW over 3 months or (d) Hgb $\le$7.5 g/dl or decrease in Hgb $\ge$3.0 g/dl, while on 500-600 mg/day AZT. The study was conducted before the commencement of an effective MAC anti-mycobacterial therapy, so the true course of MAC infection was seen without the confounder of a therapeutic regimen. Kaplan-Meier and Cox regression survival analysis was used to compare 45 MAC culture positive and 118 MAC culture negative veterans. The 1 year survival rate of veterans with documented dMAC infection was 0.37 compared to 0.50 for veterans not acquiring dMAC infection. Significant differences between subgroups were also seen with the variables: PCP prophylaxis, the AIDS indicator disease Candida esophagitis, CD4+ lymphocyte level, CD4 percent lymphocyte level, WBC level, Hgb and Hct levels. Using multivariate modeling, it was determined that PCP prophylaxis (RR = 6.12, CI 2.24-16.68) was a predictor of survival and both CD4% lymphocytes $\le$6.0% (RR = 0.33, CI 0.17-0.68) and WBC level $\le$3000 cells/mm$\sp3$ (RR = 0.60, CI 0.39-0.93) were predictors of mortality. CD4+ level $\le$50 cells/mm$\sp3$ was not a significant predictor of mortality. Although MAC culture status was a significant predictor of mortality in the univariate model, a positive dMAC culture was not a significant predictor of AIDS mortality in the multivariate model. A positive dMAC culture, however, did affect mortality in a stratified analysis when baseline laboratory values were: CD8+ lymphocytes $>$600 cells/mm$\sp3,$ Hgb $>$11.0 g/dl, Hct $>$31.0% and WBC level $>$3000 cells/mm$\sp3.$ ^

CHARACTERIZATION AND TREATMENT OF A NOVEL MOUSE MODEL OF TSC-ASSOCIATED AUTISM

Tuberous sclerosis complex (TSC) is a dominant tumor suppressor disorder caused by mutations in either TSC1 or TSC2. The proteins of these genes form a complex to inhibit the mammalian target of rapamycin complex 1 (mTORC1), which controls protein translation and cell growth. TSC causes substantial neuropathology, often leading to autism spectrum disorders (ASDs) in up to 60% of patients. The anatomic and neurophysiologic links between these two disorders are not well understood. However, both disorders share cerebellar abnormalities. Therefore, we have characterized a novel mouse model in which the Tsc2 gene was selectively deleted from cerebellar Purkinje cells (Tsc2f/-;Cre). These mice exhibit progressive Purkinje cell degeneration. Since loss of Purkinje cells is a well-reported postmortem finding in patients with ASD, we conducted a series of behavior tests to assess if Tsc2f/-;Cre mice displayed autistic-like deficits. Using the three chambered social choice assay, we found that Tsc2f/-;Cre mice showed behavioral deficits, exhibiting no preference between a stranger mouse and an inanimate object, or between a novel and a familiar mouse. Tsc2f/-;Cre mice also demonstrated increased repetitive behavior as assessed with marble burying activity. Altogether, these results demonstrate that loss of Tsc2 in Purkinje cells in a haploinsufficient background lead to behavioral deficits that are characteristic of human autism. Therefore, Purkinje cells loss and/or dysfunction may be an important link between TSC and ASD. Additionally, we have examined some of the cellular mechanisms resulting from mutations in Tsc2 leading to Purkinje cell death. Loss of Tsc2 led to upregulation of mTORC1 and increased cell size. As a consequence of increased protein synthesis, several cellular stress pathways were upregulated. Principally, these included altered calcium signaling, oxidative stress, and ER stress. Likely as a consequence of ER stress, there was also upregulation of ubiquitin and autophagy. Excitingly, treatment with an mTORC1 inhibitor, rapamycin attenuated mTORC1 activity and prevented Purkinje cell death by reducing of calcium signaling, the ER stress response, and ubiquitin. Remarkably, rapamycin treatment also reversed the social behavior deficits, thus providing a promising potential therapy for TSC-associated ASD.

THE NATURAL AND ORTHOGONAL INTERACTION (NOIA) MODELS FOR QUANTITATIVE TRAITS (QTs) AND COMPLEX DISEASES

My dissertation focuses on developing methods for gene-gene/environment interactions and imprinting effect detections for human complex diseases and quantitative traits. It includes three sections: (1) generalizing the Natural and Orthogonal interaction (NOIA) model for the coding technique originally developed for gene-gene (GxG) interaction and also to reduced models; (2) developing a novel statistical approach that allows for modeling gene-environment (GxE) interactions influencing disease risk, and (3) developing a statistical approach for modeling genetic variants displaying parent-of-origin effects (POEs), such as imprinting. In the past decade, genetic researchers have identified a large number of causal variants for human genetic diseases and traits by single-locus analysis, and interaction has now become a hot topic in the effort to search for the complex network between multiple genes or environmental exposures contributing to the outcome. Epistasis, also known as gene-gene interaction is the departure from additive genetic effects from several genes to a trait, which means that the same alleles of one gene could display different genetic effects under different genetic backgrounds. In this study, we propose to implement the NOIA model for association studies along with interaction for human complex traits and diseases. We compare the performance of the new statistical models we developed and the usual functional model by both simulation study and real data analysis. Both simulation and real data analysis revealed higher power of the NOIA GxG interaction model for detecting both main genetic effects and interaction effects. Through application on a melanoma dataset, we confirmed the previously identified significant regions for melanoma risk at 15q13.1, 16q24.3 and 9p21.3. We also identified potential interactions with these significant regions that contribute to melanoma risk. Based on the NOIA model, we developed a novel statistical approach that allows us to model effects from a genetic factor and binary environmental exposure that are jointly influencing disease risk. Both simulation and real data analyses revealed higher power of the NOIA model for detecting both main genetic effects and interaction effects for both quantitative and binary traits. We also found that estimates of the parameters from logistic regression for binary traits are no longer statistically uncorrelated under the alternative model when there is an association. Applying our novel approach to a lung cancer dataset, we confirmed four SNPs in 5p15 and 15q25 region to be significantly associated with lung cancer risk in Caucasians population: rs2736100, rs402710, rs16969968 and rs8034191. We also validated that rs16969968 and rs8034191 in 15q25 region are significantly interacting with smoking in Caucasian population. Our approach identified the potential interactions of SNP rs2256543 in 6p21 with smoking on contributing to lung cancer risk. Genetic imprinting is the most well-known cause for parent-of-origin effect (POE) whereby a gene is differentially expressed depending on the parental origin of the same alleles. Genetic imprinting affects several human disorders, including diabetes, breast cancer, alcoholism, and obesity. This phenomenon has been shown to be important for normal embryonic development in mammals. Traditional association approaches ignore this important genetic phenomenon. In this study, we propose a NOIA framework for a single locus association study that estimates both main allelic effects and POEs. We develop statistical (Stat-POE) and functional (Func-POE) models, and demonstrate conditions for orthogonality of the Stat-POE model. We conducted simulations for both quantitative and qualitative traits to evaluate the performance of the statistical and functional models with different levels of POEs. Our results showed that the newly proposed Stat-POE model, which ensures orthogonality of variance components if Hardy-Weinberg Equilibrium (HWE) or equal minor and major allele frequencies is satisfied, had greater power for detecting the main allelic additive effect than a Func-POE model, which codes according to allelic substitutions, for both quantitative and qualitative traits. The power for detecting the POE was the same for the Stat-POE and Func-POE models under HWE for quantitative traits.

Development and Characterization of an in vitro Four-species Anaerobic Dental Biofilm Model

Dental caries is the most common chronic disease worldwide. It is characterized by the demineralization of tooth enamel caused by acid produced by cariogenic dental bacteria growing on tooth surfaces, termed bacterial biofilms. Cariogenesis is a complex biological process that is influence by multiple factors and is not attributed to a sole causative agent. Instead, caries is associated with multispecies microbial biofilm communities composed of some bacterial species that directly influence the development of a caries lesion and other species that are seemingly benign but must contribute to the community in an uncharacterized way. Clinical analysis of dental caries and its microbial populations is challenging due to many factors including low sensitivity of clinical measurement tools, variability in saliva chemistry, and variation in the microbiota. Our laboratory has developed an in vitro anaerobic biofilm model for dental carries to facilitate both clinical and basic research-based analyses of the multispecies dynamics and individual factors that contribute to cariogenicity. The rational for development of this system was to improve upon the current models that lack key elements. This model places an emphasis on physiological relevance and ease of maintenance and reproducibility. The uniqueness of the model is based on integrating four critical elements: 1) a biofilm community composed of four distinct and representative species typically associated with dental caries, 2) a semi-defined synthetic growth medium designed to mimic saliva, 3) physiologically relevant biofilm growth substrates, and 4) a novel biofilm reactor device designed to facilitate the maintenance and analysis. Specifically, human tooth sections or hydroxyapatite discs embedded into poly(methyl methacrylate) (PMMA) discs are incubated for an initial 24 hr in a static inverted removable substrate (SIRS) biofilm reactor at 37°C under anaerobic conditions in artificial saliva (CAMM) without sucrose in the presence of 1 X 106 cells/ml of each Actinomyces odontolyticus, Fusobacterium nucleatum, Streptococcus mutans, and Veillonella dispar. During days 2 and 3 the samples are maintained continually in CAMM with various exposures to 0.2% sucrose; all of the discs are transferred into fresh medium every 24 hr. To validate that this model is an appropriate in vitro representation of a caries-associated multispecies biofilm, research aims were designed to test the following overarching hypothesis: an in vitro anaerobic biofilm composed of four species (S. mutans, V. dispar, A. odontolyticus, and F. nucleatum) will form a stable biofilm with a community profile that changes in response to environmental conditions and exhibits a cariogenic potential. For these experiments the biofilms as described above were exposed on days 2 and 3 to either CAMM lacking sucrose (no sucrose), CAMM with 0.2% sucrose (constant sucrose), or were transferred twice a day for 1 hr each time into 0.2% sucrose (intermittent sucrose). Four types of analysis were performed: 1) fluorescence microscopy of biofilms stained with Syto 9 and hexidium idodine to determine the biofilm architecture, 2) quantitative PCR (qPCR) to determine the cell number of each species per cm2, 3) vertical scanning interferometry (VSI) to determine the cariogenic potential of the biofilms, and 4) tomographic pH imaging using radiometric fluorescence microscopy after exposure to pH sensitive nanoparticles to measure the micro-environmental pH. The qualitative and quantitative results reveal the expected dynamics of the community profile when exposed to different sucrose conditions and the cariogenic potential of this in vitro four-species anaerobic biofilm model, thus confirming its usefulness for future analysis of primary and secondary dental caries.

Analysis of VirB4, a membrane-associated ATPase subunit essential for T -complex transport in Agrobacterium tumefaciens

Agrobacterium tumefaciens is a plant pathogen with the unique ability to export oncogenic DNA-protein complexes (T-complexes) to susceptible plant cells and cause crown gall tumors. Delivery of the T-complexes across the bacterial membranes requires eleven VirB proteins and VirD4, which are postulated to form a transmembrane transporter. This thesis examines the subcellular localization and oligomeric structure of the 87-kDa VirB4 protein, which is one of three essential ATPases proposed to energize T-complex transport and/or assembly. Results of subcellular localization studies showed that VirB4 is tightly associated with the cytoplasmic membrane, suggesting that it is a membrane-spanning protein. The membrane topology of VirB4 was determined by using a nested deletion strategy to generate random fusions between virB4 and the periplasmically-active alkaline phosphatase, $\sp\prime phoA$. Analysis of PhoA and complementary $\beta$-galactosidase reporter fusions identified two putative periplasmically-exposed regions in VirB4. A periplasmic exposure of one of these regions was further confirmed by protease susceptibility assays using A. tumefaciens spheroplasts. To gain insight into the structure of the transporter, the topological configurations of other VirB proteins were also examined. Results from hydropathy analyses, subcellular localization, protease susceptibility, and PhoA reporter fusion studies support a model that all of the VirB proteins localize at one or both of the bacterial membranes. Immunoprecipitation and Co$\sp{2+}$ affinity chromatography studies demonstrated that native VirB4 (87-kDa) and a functional N-terminally tagged HIS-VirB4 derivative (89-kDa) interact and that the interaction is independent of other VirB proteins. A $\lambda$ cI repressor fusion assay supplied further evidence for VirB4 dimer formation. A VirB4 dimerization domain was localized to the N-terminal third of the protein, as judged by: (i) transdominance of an allele that codes for this region of VirB4; (ii) co-retention of a His-tagged N-terminal truncation derivative and native VirB4 on Co$\sp{2+}$ affinity columns; and (iii) dimer formation of the N-terminal third of VirB4 fused to the cI repressor protein. Taken together, these findings are consistent with a model that VirB4 is topologically configured as an integral cytoplasmic membrane protein with two periplasmic domains and that VirB4 assembles as homodimers via an N-terminal dimerization domain. Dimer formation is postulated to be essential for stabilization of VirB4 monomers during T-complex transporter assembly. ^